Sepsis, a syndrome of systemic inflammation in response to infection, kills approximately 750,000 people in the United States every year (Angus et al. (2001) Crit Care Med 29:1303-1310). It is also the single most expensive condition treated in the US, costing the healthcare system more than $24 billion annually (Lagu et al. (2012) Crit Care Med 40:754-761); Torio and Andrews (2013) National Inpatient Hospital Costs: The Most Expensive Conditions by Payer, 2011 (Statistical Brief #160, Agency for Healthcare Research and Quality, Rockville, Md., August 2013). Prompt diagnosis and treatment of sepsis is crucial to reducing mortality, with every hour of delay increasing mortality risk (Gaieski et al. (2010) Crit Care Med 38:1045-1053; Ferrer et al. (2014) Crit Care Med 42:1749-1755). Sepsis is defined by the presence of systemic inflammatory response syndrome (SIRS), in addition to a known or suspected source of infection (Dellinger et al. (2013) Intensive Care Med 39:165-228). However, SIRS is not specific for sepsis, as sterile inflammation can arise as a nonspecific response to trauma, surgery, thrombosis, and other non-infectious insults. Thus, sepsis can be difficult to distinguish clinically from systemic inflammation caused by non-infectious sources, such as tissue trauma (Coburn et al. JAMA (2012) 308:502-511). There is no ‘gold standard’ blood test for distinguishing patients with infections at time of diagnosis, before results become available from standard microbiological cultures. One of the most common biomarkers of infection, procalcitonin, has a summary area under the receiver operating characteristic curve (AUC) of 0.78 (range 0.66-0.90) (Tang et al. (2007) Lancet Infect Dis 7:210-217; Uzzan et al. (2006) Crit Care Med 34:1996-2003; Cheval et al. (2000) Intensive Care Med 26 Suppl 2:S153-158; Ugarte et al. (1999) Crit Care Med 27:498-504). Several groups have evaluated whether cytokine or gene expression arrays can accurately diagnose sepsis; however, due to the highly variable nature of host response and human genetics, no robust diagnostic signature has been found (Cobb et al. (2009) Ann Surg 250:531-539; Xiao et al. (2011) J Exp Med 208:2581-2590; Pankla et al. (2009) Genome Biol 10:R127; Tang et al. (2009) Crit Care Med 37:882-888; Wong (2012) Crit Care 16:204; Johnson et al. (2007) Ann Surg 245:611-621). Indeed, “finding the ‘perfect’ sepsis marker has been one of the most elusive dreams in modern medicine” (Vega et al. (2009) Crit Care Med 37:1806-1807).
Both infections and tissue trauma activate many of the same innate immune receptor families, such as the Toll-like receptors and NOD-like receptors, and consequently, activate largely overlapping transcriptional pathways. Thus, distinguishing conserved downstream effects attributable solely to infections has been exceedingly difficult. Recent work has shown that there are pattern recognition receptors potentially specific to pathogen response, such as the c-type lectin, CEACAM, and siglec receptor families (Geijtenbeek et al. (2009) Nat Rev Immunol 9:465-479; Crocker (2007) Nat Rev Immunol 7:255-266; Kuespert et al. (2006) Curr Opin Cell Biol 18:565-571). Hence, it may be possible that an infection-specific immune response could be differentiated from sterile inflammation.
The ongoing search for new therapies for sepsis, and for new prognostic and diagnostic biomarkers, has generated several dozen microarray-based genome-wide expression studies over the past decade, variously focusing on diagnosis, prognosis, pathogen response, and underlying sepsis pathophysiology (Johnson et al., supra; Maslove et al. (2014) Trends Mol Med. 20(4):204-213). Despite tremendous gains in the understanding of gene expression in sepsis, few insights have translated to improvements in clinical practice. Importantly, many of these studies have been deposited into public repositories such as the NIH Gene Expression Omnibus (GEO) and ArrayExpress, and thus there is now a wealth of publically available data on sepsis. In particular, there are several studies comparing patients with sepsis to patients with non-infectious inflammation (such as SIRS) that occurs after major surgery, traumatic injury, or in non-sepsis-related ICU admission (thrombosis, respiratory failure, etc.).
One dataset in particular, the Inflammation and Host Response to Injury Program (Glue Grant) (Cobb et al. (2005) Proc Natl Acad Sci USA 102:4801-4806), has yielded several important findings about the effects of time on gene expression after trauma and in sepsis. One part of the Glue Grant longitudinally examined gene expression in patients after severe traumatic injuries. Several groups have examined these data with respect to time; notable findings are that (1) more than 80% of expressed genes show differential expression after traumatic injury (Xiao et al., supra), (2) different clusters of genes recover over markedly different time periods (Seok et al. (2013) Proc Natl Acad Sci USA 110:3507-3512), (3) differing scenarios of inflammation such as trauma, burns, and endotoxicosis exhibit similar gene expression changes (Seok et al., supra), and (4) the extent to which post-trauma gene expression profiles differ from those of healthy patients, and their degree of gene expression recovery over time, are correlated with clinical outcomes (Desai et al. (2011) PLoS Med 8:e1001093; Warren et al. (2009) Mol Med 15:220-227). There is thus growing understanding of the importance of the changes that underlie recovery from trauma, and their impact on specific clinical outcomes.
There remains a need for sensitive and specific diagnostic tests for sepsis that can distinguish sepsis from noninfectious sources of inflammation, such as caused by traumatic injury and SIRS.